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From Trash to Cash: How Blockchain and Multi-Sensor-Driven Artificial Intelligence Can Transform Circular Economy of Plastic Waste?
- Source :
- Administrative Sciences, Vol 10, Iss 23, p 23 (2020), Administrative Sciences, Volume 10, Issue 2
- Publication Year :
- 2020
- Publisher :
- MDPI AG, 2020.
-
Abstract
- Virgin polymers based on petrochemical feedstock are mainly preferred by most plastic goods manufacturers instead of recycled plastic feedstock. Major reason for this is the lack of reliable information about the quality, suitability, and availability of recycled plastics, which is partly due to lack of proper segregation techniques. In this paper, we present our ongoing efforts to segregate plastics based on its types and improve the reliability of information about recycled plastics using the first-of-its-kind blockchain smart contracts powered by multi-sensor data-fusion algorithms using artificial intelligence. We have demonstrated how different data-fusion modes can be employed to retrieve various physico-chemical parameters of plastic waste for accurate segregation. We have discussed how these smart tools help in efficiently segregating commingled plastics and can be reliably used in the circular economy of plastic. Using these tools, segregators, recyclers, and manufacturers can reliably share data, plan the supply chain, execute purchase orders, and hence, finally increase the use of recycled plastic feedstock.
- Subjects :
- blockchain
Plastic recycling
Computer science
plastic recycling
020209 energy
Reliability (computer networking)
Supply chain
media_common.quotation_subject
02 engineering and technology
010501 environmental sciences
Raw material
waste segregation
smart contracts
01 natural sciences
plastic waste
ddc:350
0202 electrical engineering, electronic engineering, information engineering
Quality (business)
landfills
multi-sensor
0105 earth and related environmental sciences
media_common
data fusion
Purchase order
business.industry
Circular economy
circular economy
waste-to-value
Sensor fusion
artificial intelligence
sustainability
General Business, Management and Accounting
lcsh:Political institutions and public administration (General)
AI
lcsh:JF20-2112
Artificial intelligence
business
Subjects
Details
- Language :
- English
- ISSN :
- 20763387
- Volume :
- 10
- Issue :
- 23
- Database :
- OpenAIRE
- Journal :
- Administrative Sciences
- Accession number :
- edsair.doi.dedup.....400cc3fee69e64bdca1915bbb3cc3403